Bioethanol Production from Lignocellulosic Biomass

An overview of the basic technology to produce bioethanol from lignocellulosic biomass is presented in this context. The conventional process includes two main steps. First, lignocellulose must be pretreated in order to remove lignin and enhance the penetration of hydrolysis agents without chemically destruction of cellulose and hemicellulose. Second, the pretreated material is converted to bioethanol by hydrolysis and fermentation. Some typical published studies and popular processing methods in attempts to improve the biomass conversion to bioethanol and increase the cost-effectiveness are also introduced briefly. Herein, the refinery of the resulted raw bioethanol mixture to obtain higher concentrated solution is not regarded

Chemical diversity of essential oils of rhizomes of six species of Zingiberaceae family

In this study, the essential oils from the rhizomes of six species belonging to the Zingiberaceae family, including Zingiber zerumbet, Curcuma pierreana, Globba macrocarpa, Alpinia conchigera, Stahlianthus campanulatus and Amomum sp., collected in Binh Chau-Phuoc Buu Nature Reserve were isolated using hydrodistillation, and their constituents were identified via Gas Chromatography-Mass Spectrometry. A total of 91 constituents have been identified from essential oils. These compounds were classified into 4 clusters by Agglomerative Hierarchical Clustering (AHC) and Principal Component Analysis (PCA) analysis. The principal constituents of the essential oils isolated from four species, C. pierreana, S. campanulatus, A. conchigera, and Z. zerumbet contained camphene (18.82%), α-copaene (11.75%), p-xylene (21.86%), and α-santalene (17.91%), which were significantly different from those in previous reports. Furthermore, this study revealed the chemical constituents of essential oils of G. macrocarpa and Amomum sp. for the first time. Accordingly, artemisia triene (22.21%), β-pinene (13.57%), 4,6,8-trimethylazulene (11.1%), 2-tert-butylquinoline (9.86%), β-patchoulene (7.06%), α-elemene (6.93%), and β-ocimene (6.0%) were the major compounds in essential oils of G. macrocarpa rhizomes whereas the oil of Amomum sp. was found to be rich in 2-carene (21.82%), fenchyl acetate (14.26%), 3-carene (8.28%), bornyl acetate (7.7%), and D-limonene (7.13%)

Ultimate pretreatment of lignocellulose in bioethanol production by combining both acidic and alkaline pretreatment

Alkaline pretreatment has been known as the most popular method to process lignocellulosic materials for bioethanol production due to its simplicity and high efficiency. However, the waste water of the process has a very high basicity, which requires neutralization with acids upon further disposal. In this study, rubber wood saw dust (Hevea brasiliensis) was employed as lignocellulosic material and its pretreatment was inspected with both diluted H2SO4 and NaOH in different combination ways. Hereby, acid was used not only for waste water neutralization but also to contribute to lignin removal. Analysis results showed that an aqueous solution of 2.0 - 2.5 wt.% H2SO4 can be used to treat the biomass followed by alkaline pretreatment. By this so-called combo-pretreatment technique, cellulose was well preserved without significant hydrolysis while the final pretreatment efficiency was up to 63.0%, compared to 48.2% of using only the alkaline solution and 13.7% of using only the acidic solution. Finally, alkaline waste water can be mixed to be neutralized with acidic waste water from the two previous steps. This innovated technique improved the pretreatment efficiency almost without increasing in chemical cost

River Report. State of the Lower St. Johns River Basin, Florida: Water Quality, Fisheries, Aquatic Life, Contaminants, 2022.

https://digitalcommons.unf.edu/sotr/1012/thumbnail.jp

TextANIMAR: Text-based 3D Animal Fine-Grained Retrieval

3D object retrieval is an important yet challenging task, which has drawn more and more attention in recent years. While existing approaches have made strides in addressing this issue, they are often limited to restricted settings such as image and sketch queries, which are often unfriendly interactions for common users. In order to overcome these limitations, this paper presents a novel SHREC challenge track focusing on text-based fine-grained retrieval of 3D animal models. Unlike previous SHREC challenge tracks, the proposed task is considerably more challenging, requiring participants to develop innovative approaches to tackle the problem of text-based retrieval. Despite the increased difficulty, we believe that this task has the potential to drive useful applications in practice and facilitate more intuitive interactions with 3D objects. Five groups participated in our competition, submitting a total of 114 runs. While the results obtained in our competition are satisfactory, we note that the challenges presented by this task are far from being fully solved. As such, we provide insights into potential areas for future research and improvements. We believe that we can help push the boundaries of 3D object retrieval and facilitate more user-friendly interactions via vision-language technologies.Comment: arXiv admin note: text overlap with arXiv:2304.0573

Wearable devices for remote monitoring of hospitalized patients with COVID-19 in Vietnam

Patients with severe COVID-19 disease require monitoring with pulse oximetry as a minimal requirement. In many low- and middle- income countries, this has been challenging due to lack of staff and equipment. Wearable pulse oximeters potentially offer an attractive means to address this need, due to their low cost, battery operability and capacity for remote monitoring. Between July and October 2021, Ho Chi Minh City experienced its first major wave of SARS-CoV-2 infection, leading to an unprecedented demand for monitoring in hospitalized patients. We assess the feasibility of a continuous remote monitoring system for patients with COVID-19 under these circumstances as we implemented 2 different systems using wearable pulse oximeter devices in a stepwise manner across 4 departments

Analytical applications of nanostructured plasmonic crystals

Surface plasmon resonances (SPR) have been exploited through various means for the realization of label-free, surface-sensitive chemical analysis and imaging, all of which rely on the interactions between the local environment and the evanescent electric fields generated by the surface plasmons at the metal-dielectric interface. Plasmonic crystals are a versatile platform for the tunable coupling of light into surface plasmon modes, and soft nanoimprint lithography represents a class of fabrication techniques capable of inexpensive, high fidelity replication of nanoscale features over large areas; these methods are well-matched for surface-enhanced sensing applications whose performance depends strongly on these fabrication characteristics. The work presented in this dissertation focused on the development of new surface-enhanced Raman spectroscopy and surface plasmon resonance imaging modalities based on this nanostructured plasmonic crystal platform. Nanostructured plasmonic crystals were patterned onto the tips of silica optical fibers using a soft embossing method for use as single-fiber SERS optrodes, and enhanced Raman scattering was observed for benzenethiol monolayers adsorbed onto the structured fiber tip as well as for Rhodamine 6G dissolved in aqueous solution. The inherent versatility of this plasmonic platform for SERS-based sensing was demonstrated through the effective Raman enhancements obtained in markedly different refractive index environments. Nanoimprinted plasmonic crystals were also adapted for reflection imaging studies of thin films deposited onto the metal surface. Normalized contrast metrics were developed based on reflection images of polyelectrolyte layer-by-layer assemblies acquired using bandpass filters to restrict the accessible wavelength ranges and quantitatively calibrated to the surface film thickness. As a model system, Aplysia pedal neurons were cultured on the plasmonic crystal surface, and the thicknesses of neuronal processes were quantitated using the calibrations derived for this reflection imaging protocol using common laboratory equipment: a reflection microscope, commercially available bandpass filters, and a digital camera. The imaging-based measurements of neuronal process thickness were verified independently using atomic force microscopy with excellent agreement between the two methods. The applications explored in this dissertation demonstrate the broader utility of nanoimprinted plasmonic crystals for chemical sensing and imaging

Fuel Mixture Nonconvex Optimization Problem: Solution Methods and Numerical Simulations

International audienc

On globally solving linearly constrained indefinite quadratic minimization problems by decomposition branch and bound method

International audienceThe global minimization ofan indefinite quadratic function over a bounded polyhedralset using a décomposition branch and bound approach is considered. The objective functionconsists ofan unseparated convex part and a separated concave part The large-scale problems arecharacterized by hoving the number of convex variables much more thon that of concave variables.The advantages of the method is that it uses the rectangular subdivision on the subspace of concavevariables. Using a easily constmcted convex underestimating function îo the objective function,a lower bound is obtained by solving a convex quadratic programming problem. Three variantsusing exhaustive, adaptive and w-subdivision are discussed. Computational results are presentedfor problems with 10-20 concave variables and up to 200 convex variables.La minimisation globale d'une forme quadratique indéfinie sur un polyèdre convexeborné par une méthode décomposition-séparation et évaluation est étudiée dans ce papier. Lafonction objectif est la somme d'une forme quadratique convexe et d'une forme quadratique concaveséparable en ses variables. Les problèmes de grande dimension sont caractérisés par le fait quele nombre des variables convexes est beaucoup plus grand que celui des variables concaves.L'avantage de la méthode réside dans l'utilisation de la subdivision rectangulaire uniquementdans le sous-espace des variables concaves. A l'aide d'une minorante très simple à calculer de lapartie concave, une borne inférieure est obtenue en résolvant un programme quadratique convexe.Trois variantes utilisant la subdivision exhautive, la subdivision adaptive et la w-subdivision sontconsidérées. Les simulations numériques sont présentés pour les problèmes ayant 10-20 variablesconcaves et jusqu'à 200 variables convexes